1. Field of the Invention
The present invention relates to an apparatus which is arranged to recognize the motion of an object contained in an image signal which is mechanically read out, as well as to an image extracting apparatus capable of discriminating between unnecessary information (such as the "background" contained in an image signal) and useful information (such as a "moving object" hidden in the background) to extract the useful information alone. More specifically, the present invention relates to a system for extracting a "meaningful" object from input image data or carrying out measurement of the number, the dimensions, the area, etc. of the extracted "meaningful" object or for effecting pattern processing to discriminate between an object and any matter other than the object in input image data on the basis of the feature of the object, thereby classifying them into separate categories. In addition, the present invention relates to a holonic computer.
2. Description of the Related Art
In a wide range of industrial fields, there has recently been a strong demand for information processing systems for extracting useful (or meaningful) data from a large amount of input data such as input motion-image data or for selectively processing a specific object contained in a large amount of input data. This demand has been increasing in a situation in which, although image data obtained through, e.g. a camera is the most easily available, it is difficult to avoid the problem that the obtained data necessarily contains, in its primitive form, a large amount of unorganized and meaningless information.
FIG. 23 shows in block form a so-called pattern processing system or pattern measuring system which has heretofore been reduced to practice. The illustrated conventional type of pattern processing system is generally constituted by an input section 200, a processing section 201, a memory section 202, and an output section 203. The primary recent trend in such a conventional arrangement is to use a digital computer as the processing section 201. The input section 200 is arranged to divide an input image signal into a multiplicity of parts, for example, break down an input motion image into fine picture elements, and transfer the divided parts to the processing section 201 for data-processing purposes. The processing section 201 incorporates a method which comprises the steps of computing and extracting various kinds of features of all the input data, retrieving a feature inherent in an object, and identifying the object of interest. In addition, the processing section 201 compares the feature obtained by a combination of such partial features and the feature of the entire object stored in the memory section 202, thereby implementing recognition of the object.
Basically, the conventional process described above is performed by using all local data contained in an input image. However, it has also been common practice to adopt information compression techniques, for example, a method of regularly eliminating input information in order to reduce the amount of information to be processed, or a method of reducing the amount of hardware used for process execution and representing input information in a multiplexed form in order to achieve a more rapid process. The use of the information compression techniques contemplates the overall enhancement of processing efficiency. Furthermore, to meet industrial demands in which an increase in the speed of processing of an enormous amount of complicated data is primarily desired, on the assumption that the above-described arrangements and methods are used, the prior arts have proposed increases in the operating speed and the capacity of hardware which constitutes parts of the system, and modifications of the algorithms used in a process such as an arithmetic-logic process and a retrieving process, as well as specialization techniques such as restriction of the range of an object which is derived from information to be treated and specification of the kind of object.
In such conventional types of processing techniques, however, it is impossible to avoid shortcomings such as increases in the scale and the price of hardware, restrictions imposed upon processing speed due to the limitations of hardware techniques, and the deterioration of resolution resulting from an increase in processing speed. In addition, it has been difficult to recognize the "overall feature" of an input image including a figure of complicated form or a plurality of patterns by using the conventional method in which a simple combination of local data ("partial feature") is regarded as "overall feature", since the conventional method cannot identify the "overall feature" by means of the simple combination of "partial feature".
This suggests that, in order to extract meaningful information and eliminate unnecessary information from physical signals representing a motion image, it is necessary to develop a "motion recognition apparatus" having a novel structure based on a new technical concept. In other words, in order to eliminate unnecessary information from an image signal containing a large amount of unwanted information, it is first of all necessary to extract the overall "meaning" of the image from the image signal and, if the extraction is accomplished, it will then be possible to determine, on the basis of the overall "meaning", whether or not the image signal is useful.